DOCSLIB.ORG

Closures (Implementing Higher Order Functions)

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Closures (Implementing Higher Order Functions) CMSC 330: Organization of Programming Languages Closures (Implementing Higher Order Functions) CMSC 330 - Spring 2020 1 Returning Functions as Results In OCaml you can pass functions as arguments • to map, fold, etc. and you can return functions as results # let pick_fn n = let plus_three x = x + 3 in let plus_four x = x + 4 in if n > 0 then plus_three else plus_four val pick_fn : int -> (int->int) = <fun> Here, pick_fn takes an int argument, and returns a function # let g = pick_fn 2;; val g : int -> int = <fun> # g 4;; (* evaluates to 7 *) CMSC 330 - Spring 2020 2 Multi-argument Functions Consider a rewriting of the prior code (above) let pick_fn n = if n > 0 then (fun x->x+3) else (fun x->x+4) Here’s another version let pick_fn n = (fun x -> if n > 0 then x+3 else x+4) … the shorthand for which is just let pick_fn n x = if n > 0 then x+3 else x+4 I.e., a multi-argument function! CMSC 330 - Spring 2020 3 Currying We just saw a way for a function to take multiple arguments! • I.e., no separate concept of multi-argument functions – can encode one as a function that takes a single argument and returns a function that takes the rest This encoding is called currying the function • Named after the logician Haskell B. Curry • But Schönfinkel and Frege discovered it Ø So maybe it should be called Schönfinkelizing or Fregging CMSC 330 - Spring 2020 4 Curried Functions In OCaml OCaml syntax defaults to currying. E.g., let add x y = x + y • is identical to all of the following: let add = (fun x -> (fun y -> x + y)) let add = (fun x y -> x + y) let add x = (fun y -> x+y) Thus: • add has type int -> (int -> int) • add 3 has type int -> int Ø add 3 is a function that adds 3 to its argument • (add 3) 4 = 7 This works for any number of arguments CMSC 330 - Spring 2020 5 Syntax Conventions for Currying Because currying is so common, OCaml uses the following conventions: • -> associates from the right Ø Thus int -> int -> int is the same as Ø int -> (int -> int) • function application associates from the left Ø Thus add 3 4 is the same as Ø (add 3) 4 CMSC 330 - Spring 2020 7 Quiz 1: Which f definition is equivalent? let f a b = a / b;; A. let f b = fun a -> a / b;; B. let f = fun a | b -> a / b;; C. let f (a, b) = a / b;; D. let f = fun a -> (fun b -> a / b);; CMSC 330 - Spring 2020 8 Quiz 1: Which f definition is equivalent? let f a b = a / b;; A. let f b = fun a -> a / b;; B. let f = fun a | b -> a / b;; C. let f (a, b) = a / b;; D. let f = fun a -> (fun b -> a / b);; CMSC 330 - Spring 2020 9 Quiz 2: What is enabled by currying? A. Passing functions as arguments B. Passing only a portion of the expected arguments C. Naming arguments D. Recursive functions CMSC 330 - Spring 2020 10 Quiz 2: What is enabled by currying? A. Passing functions as arguments B. Passing only a portion of the expected arguments C. Naming arguments D. Recursive functions CMSC 330 - Spring 2020 11 Multiple Arguments, Partial Application Another way you could encode support for multiple arguments is using tuples • let f (a,b) = a / b (* int*int -> int *) • let f a b = a / b (* int-> int-> int *) Is there a benefit to using currying instead? • Supports partial application – useful when you want to provide some arguments now, the rest later • let add a b = a + b;; • let addthree = add 3;; • addthree 4;; (* evaluates to 7 *) CMSC 330 - Spring 2020 13 Currying is Standard In OCaml Pretty much all functions are curried • Like the standard library map, fold, etc. • See /usr/local/ocaml/lib/ocaml on Grace Ø In particular, look at the file list.ml for standard list functions Ø Access these functions using List.<fn name> Ø E.g., List.hd, List.length, List.map OCaml works hard to make currying efficient • Because otherwise it would do a lot of useless allocation and destruction of closures • What are those, you ask? Let’s see … CMSC 330 - Spring 2020 14 Closure CMSC 330 - Spring 2020 18 Java Example public class Test{ public void doSomething(){ int a = 10; //must be final Runnable runnable = new Runnable(){ Needed later, public void run(){ makes copy of a int b = a + 1; System.out.println(b); } }; (new Thread(runnable)).start(); //runs later //a = 100; //not allowed } public static void main(String[] args){ Test t = new Test(); t.doSomething(); } }// a=10 is removed from the stack here CMSC 330 - Spring 2020 19 OCaml Example let foo x = let bar y = x + y in bar ;; foo 10 = ? (fun y -> x + y) ? Where is x? CMSC 330 - Spring 2020 20 Another Example let x = 1 in let f = fun y -> x in let x = 2 in f 0 What does this expression should evaluate to? A. 1 B. 2 CMSC 330 - Spring 2020 21 Another Example let x = 1 in let f = fun y -> x in let x = 2 in f 0 What does this expression should evaluate to? A. 1 B. 2 CMSC 330 - Spring 2020 22 Scope Dynamic scope • The body of a function is evaluated in the current dynamic environment at the time the function is called, not the old dynamic environment that existed at the time the function was defined. Lexical scope • The body of a function is evaluated in the old dynamic environment that existed at the time the function was defined, not the current environment when the function is called. CMSC 330 - Spring 2020 23 Closure let foo x = let x = 1 in let bar y = x + y in let f = fun y -> x in bar ;; let x = 2 in f 0 bar 3 Closure Closure Function Environment Function Environment CMSC 330 - Spring 2020 24 Closures Implement Static Scoping An environment is a mapping from variable names to values • Just like a stack frame A closure is a pair (f, e) consisting of function code f and an environment e When you invoke a closure, f is evaluated using e to look up variable bindings CMSC 330 - Spring 2020 25 Example – Closure 1 let add x = (fun y -> x + y) (add 3) 4 → <cl> 4 → 3 + 4 → 7 Closure Function Environment CMSC 330 - Spring 2020 26 Example – Closure 2 let mult_sum (x, y) = let z = x + y in fun w -> w * z (mult_sum (3, 4)) 5 → <cl> 5 → 5 * 7 → 35 CMSC 330 - Spring 2020 27 Quiz 3: What is x? let a = 1;; let a = 0;; let b = 10;; let f () = a + b;; let b = 5;; let x = f ();; A. 10 B. 1 C. 15 D. Error - variable name conflicts CMSC 330 - Spring 2020 28 Quiz 3: What is x? let a = 1;; let a = 0;; let b = 10;; let f () = a + b;; let b = 5;; let x = f ();; A. 10 B. 1 C. 15 D. Error - variable name conflicts CMSC 330 - Spring 2020 29 Quiz 4: What is z? let f x = fun y -> x – y in let g = f 2 in let x = 3 in let z = g 4 in z;; A. 7 B. -2 C. -1 D. Type Error – insufficient arguments CMSC 330 - Spring 2020 30 Quiz 4: What is z? let f x = fun y -> x – y in let g = f 2 in let x = 3 in let z = g 4 in z;; A. 7 B. -2 C. -1 D. Type Error – insufficient arguments CMSC 330 - Spring 2020 31 Quiz 5: What does this evaluate to? let f x = x+1 in let g = f in g (fun i -> i+1) 1 A. Type Error B. 1 C. 2 D. 3 CMSC 330 - Spring 2020 32 Quiz 5: What does this evaluate to? let f x = x+1 in let g = f in (g (fun i -> i+1)) 1 A. Type Error – Too many arguments passed to g (application is left associative) B. 1 C. 2 D. 3 CMSC 330 - Spring 2020 33 Higher-Order Functions in C C supports function pointers typedef int (*int_func)(int); void app(int_func f, int *a, int n) { for (int i = 0; i < n; i++) a[i] = f(a[i]); } int add_one(int x) { return x + 1; } int main() { int a[] = {5, 6, 7}; app(add_one, a, 3); } CMSC 330 - Spring 2020 34 Higher-Order Functions in C (cont.) C does not support closures • Since no nested functions allowed • Unbound symbols always in global scope int y = 1; void app(int(*f)(int), n) { return f(n); } int add_y(int x) { return x + y; } int main() { app(add_y, 2); } CMSC 330 - Spring 2020 35 Higher-Order Functions in C (cont.) Cannot access non-local variables in C OCaml code let add x y = x + y Equivalent code in C is illegal int (* add(int x))(int) { return add_y; } int add_y(int y) { return x + y; /* error: x undefined */ } CMSC 330 - Spring 2020 36 Higher-Order Functions in C (cont.) OCaml code let add x y = x + y Works if C supports nested functions • Not in ISO C, but in gcc; but not allowed to return them int (* add(int x))(int) { int add_y(int y) { return x + y; } return add_y; } • Does not allocate closure, so x popped from stack and add_y will get garbage (potentially) when called CMSC 330 - Spring 2020 37 Java 8 Supports Lambda Expressions Ocaml’s fun (a, b) -> a + b Is like the following in Java 8 (a, b) -> a + b Java 8 supports closures, and variations on this syntax CMSC 330 - Spring 2020 38 Java 8 Example public class Calculator { interface IntegerMath { int operation(int a, int b); } public int operateBinary(int a, int b, IntegerMath op) { return op.operation(a, b); } public static void main(String..
Load more

Recommended publications
  • Lecture 4. Higher-Order Functions Functional Programming
    Lecture 4. Higher-order functions Functional Programming [Faculty of Science Information and Computing Sciences] 0 I function call and return as only control-flow primitive I no loops, break, continue, goto I (almost) unique types I no inheritance hell I high-level declarative data-structures I no explicit reference-based data structures Goal of typed purely functional programming Keep programs easy to reason about by I data-flow only through function arguments and return values I no hidden data-flow through mutable variables/state [Faculty of Science Information and Computing Sciences] 1 I (almost) unique types I no inheritance hell I high-level declarative data-structures I no explicit reference-based data structures Goal of typed purely functional programming Keep programs easy to reason about by I data-flow only through function arguments and return values I no hidden data-flow through mutable variables/state I function call and return as only control-flow primitive I no loops, break, continue, goto [Faculty of Science Information and Computing Sciences] 1 I high-level declarative data-structures I no explicit reference-based data structures Goal of typed purely functional programming Keep programs easy to reason about by I data-flow only through function arguments and return values I no hidden data-flow through mutable variables/state I function call and return as only control-flow primitive I no loops, break, continue, goto I (almost) unique types I no inheritance hell [Faculty of Science Information and Computing Sciences] 1 Goal
    [Show full text]
  • Higher-Order Functions 15-150: Principles of Functional Programming – Lecture 13
    Higher-order Functions 15-150: Principles of Functional Programming { Lecture 13 Giselle Reis By now you might feel like you have a pretty good idea of what is going on in functional program- ming, but in reality we have used only a fragment of the language. In this lecture we see what more we can do and what gives the name functional to this paradigm. Let's take a step back and look at ML's typing system: we have basic types (such as int, string, etc.), tuples of types (t*t' ) and functions of a type to a type (t ->t' ). In a grammar style (where α is a basic type): τ ::= α j τ ∗ τ j τ ! τ What types allowed by this grammar have we not used so far? Well, we could, for instance, have a function below a tuple. Or even a function within a function, couldn't we? The following are completely valid types: int*(int -> int) int ->(int -> int) (int -> int) -> int The first one is a pair in which the first element is an integer and the second one is a function from integers to integers. The second one is a function from integers to functions (which have type int -> int). The third type is a function from functions to integers. The two last types are examples of higher-order functions1, i.e., a function which: • receives a function as a parameter; or • returns a function. Functions can be used like any other value. They are first-class citizens. Maybe this seems strange at first, but I am sure you have used higher-order functions before without noticing it.
    [Show full text]
  • Clojure, Given the Pun on Closure, Representing Anything Specific
    dynamic, functional programming for the JVM “It (the logo) was designed by my brother, Tom Hickey. “It I wanted to involve c (c#), l (lisp) and j (java). I don't think we ever really discussed the colors Once I came up with Clojure, given the pun on closure, representing anything specific. I always vaguely the available domains and vast emptiness of the thought of them as earth and sky.” - Rich Hickey googlespace, it was an easy decision..” - Rich Hickey Mark Volkmann [email protected] Functional Programming (FP) In the spirit of saying OO is is ... encapsulation, inheritance and polymorphism ... • Pure Functions • produce results that only depend on inputs, not any global state • do not have side effects such as Real applications need some changing global state, file I/O or database updates side effects, but they should be clearly identified and isolated. • First Class Functions • can be held in variables • can be passed to and returned from other functions • Higher Order Functions • functions that do one or both of these: • accept other functions as arguments and execute them zero or more times • return another function 2 ... FP is ... Closures • main use is to pass • special functions that retain access to variables a block of code that were in their scope when the closure was created to a function • Partial Application • ability to create new functions from existing ones that take fewer arguments • Currying • transforming a function of n arguments into a chain of n one argument functions • Continuations ability to save execution state and return to it later think browser • back button 3 ..
    [Show full text]
  • Topic 6: Partial Application, Function Composition and Type Classes
    Recommended Exercises and Readings Topic 6: Partial Application, • From Haskell: The craft of functional programming (3rd Ed.) Function Composition and Type • Exercises: • 11.11, 11.12 Classes • 12.30, 12.31, 12.32, 12.33, 12.34, 12.35 • 13.1, 13.2, 13.3, 13.4, 13.7, 13.8, 13.9, 13.11 • If you have time: 12.37, 12.38, 12.39, 12.40, 12.41, 12.42 • Readings: • Chapter 11.3, and 11.4 • Chapter 12.5 • Chapter 13.1, 13.2, 13.3 and 13.4 1 2 Functional Forms Curried and Uncurried Forms • The parameters to a function can be viewed in two different ways • Uncurried form • As a single combined unit • Parameters are bundled into a tuple and passed as a group • All values are passed as one tuple • Can be used in Haskell • How we typically think about parameter passing in Java, C++, Python, Pascal, C#, … • Typically only when there is a specific need to do • As a sequence of values that are passed one at a time • As each value is passed, a new function is formed that requires one fewer parameters • Curried form than its predecessor • Parameters are passed to a function sequentially • How parameters are passed in Haskell • Standard form in Haskell • But it’s not a detail that we need to concentrate on except when we want to make use of it • Functions can be transformed from one form to the other 3 4 Curried and Uncurried Forms Curried and Uncurried Forms • A function in curried form • Why use curried form? • Permits partial application multiply :: Int ‐> Int ‐> Int • Standard way to define functions in Haskell multiply x y = x * y • A function of n+1
    [Show full text]
  • Functional Programming Lecture 1: Introduction
    Functional Programming Lecture 13: FP in the Real World Viliam Lisý Artificial Intelligence Center Department of Computer Science FEE, Czech Technical University in Prague [email protected] 1 Mixed paradigm languages Functional programming is great easy parallelism and concurrency referential transparency, encapsulation compact declarative code Imperative programming is great more convenient I/O better performance in certain tasks There is no reason not to combine paradigms 2 3 Source: Wikipedia 4 Scala Quite popular with industry Multi-paradigm language • simple parallelism/concurrency • able to build enterprise solutions Runs on JVM 5 Scala vs. Haskell • Adam Szlachta's slides 6 Is Java 8 a Functional Language? Based on: https://jlordiales.me/2014/11/01/overview-java-8/ Functional language first class functions higher order functions pure functions (referential transparency) recursion closures currying and partial application 7 First class functions Previously, you could pass only classes in Java File[] directories = new File(".").listFiles(new FileFilter() { @Override public boolean accept(File pathname) { return pathname.isDirectory(); } }); Java 8 has the concept of method reference File[] directories = new File(".").listFiles(File::isDirectory); 8 Lambdas Sometimes we want a single-purpose function File[] csvFiles = new File(".").listFiles(new FileFilter() { @Override public boolean accept(File pathname) { return pathname.getAbsolutePath().endsWith("csv"); } }); Java 8 has lambda functions for that File[] csvFiles = new File(".")
    [Show full text]
  • Notes on Functional Programming with Haskell
    Notes on Functional Programming with Haskell H. Conrad Cunningham [email protected] Multiparadigm Software Architecture Group Department of Computer and Information Science University of Mississippi 201 Weir Hall University, Mississippi 38677 USA Fall Semester 2014 Copyright c 1994, 1995, 1997, 2003, 2007, 2010, 2014 by H. Conrad Cunningham Permission to copy and use this document for educational or research purposes of a non-commercial nature is hereby granted provided that this copyright notice is retained on all copies. All other rights are reserved by the author. H. Conrad Cunningham, D.Sc. Professor and Chair Department of Computer and Information Science University of Mississippi 201 Weir Hall University, Mississippi 38677 USA [email protected] PREFACE TO 1995 EDITION I wrote this set of lecture notes for use in the course Functional Programming (CSCI 555) that I teach in the Department of Computer and Information Science at the Uni- versity of Mississippi. The course is open to advanced undergraduates and beginning graduate students. The first version of these notes were written as a part of my preparation for the fall semester 1993 offering of the course. This version reflects some restructuring and revision done for the fall 1994 offering of the course|or after completion of the class. For these classes, I used the following resources: Textbook { Richard Bird and Philip Wadler. Introduction to Functional Program- ming, Prentice Hall International, 1988 [2]. These notes more or less cover the material from chapters 1 through 6 plus selected material from chapters 7 through 9. Software { Gofer interpreter version 2.30 (2.28 in 1993) written by Mark P.
    [Show full text]
  • Currying and Partial Application and Other Tasty Closure Recipes
    CS 251 Fall 20192019 Principles of of Programming Programming Languages Languages λ Ben Wood Currying and Partial Application and other tasty closure recipes https://cs.wellesley.edu/~cs251/f19/ Currying and Partial Application 1 More idioms for closures • Function composition • Currying and partial application • Callbacks (e.g., reactive programming, later) • Functions as data representation (later) Currying and Partial Application 2 Function composition fun compose (f,g) = fn x => f (g x) Closure “remembers” f and g : ('b -> 'c) * ('a -> 'b) -> ('a -> 'c) REPL prints something equivalent ML standard library provides infix operator o fun sqrt_of_abs i = Math.sqrt(Real.fromInt(abs i)) fun sqrt_of_abs i = (Math.sqrt o Real.fromInt o abs) i val sqrt_of_abs = Math.sqrt o Real.fromInt o abs Right to left. Currying and Partial Application 3 Pipelines (left-to-right composition) “Pipelines” of functions are common in functional programming. infix |> fun x |> f = f x fun sqrt_of_abs i = i |> abs |> Real.fromInt |> Math.sqrt (F#, Microsoft's ML flavor, defines this by default) Currying and Partial Application 4 Currying • Every ML function takes exactly one argument • Previously encoded n arguments via one n-tuple • Another way: Take one argument and return a function that takes another argument and… – Called “currying” after logician Haskell Curry Currying and Partial Application 6 Example val sorted3 = fn x => fn y => fn z => z >= y andalso y >= x val t1 = ((sorted3 7) 9) 11 • Calling (sorted3 7) returns a closure with: – Code fn y => fn z
    [Show full text]
  • Lecture Notes on First-Class Functions
    Lecture Notes on First-Class Functions 15-411: Compiler Design Rob Simmons and Jan Hoffmann Lecture 25 Nov 29, 2016 1 Introduction In this lecture, we discuss two generalizations of C0: function pointers and nested, anonymous functions (lambdas). As a language feature, nested functions are a nat- ural extension of function pointers. However, because of the necessity of closures in the implementation of nested functions, the necessary implementation strategies are somewhat different. 2 Function pointers The C1 language includes a concept of function pointers, which are obtained from a function with the address-of operator &f. The dynamic semantics can treat &f as a new type of constant, which represents the memory address where the function f is stored. S; η ` (∗e)(e1; e2) B K −! S; η ` e B ((∗_)(e1; e2) ;K) S; η ` &f B ((∗_)(e1; e2);K) −! S; η ` e1 B (f(_; e2) ;K) Again, we only show the special case of evaluation function calls with two and zero arguments. After the second instruction, we continue evaluating the argu- ments to the function left-to-right and then call the function as in our previous dynamics. We do not have to model function pointers using a heap as we did for arrays and pointers since we are not able to change the functions that is stored at a given address. It is relatively straightforward to extend a language with function pointers, be- cause they are addresses. We can obtain that address at runtime by referring to the label as a constant. Any label labl in an assembly file represents an address in memory (since the program must be loaded into memory in order to run), and can LECTURE NOTES NOV 29, 2016 First-Class Functions L25.2 be treated as a constant by writing $labl.
    [Show full text]
  • Ml-Curry-4Up.Pdf
    CS 251 SpringFall 2019 2020 Principles of of Programming Programming Languages Languages Ben Wood More idioms for closures λ Ben Wood • Function composition Currying • Currying and partial application and Partial Application • Callbacks (e.g., reactive programming, later) and other tasty closure recipes • Functions as data representation (later) https://cs.wellesley.edu/~cs251/s20/ Currying and Partial Application 1 Currying and Partial Application 2 Function composition (right-to-left) Pipelines (left-to-right composition) fun compose (f,g) = fn x => f (g x) Common in functional programming. Closure “remembers” f and g : ('b -> 'c) * ('a -> 'b) -> ('a -> 'c) infix |> REPL prints something equivalent fun x |> f = f x fun sqrt_of_abs i = ML standard library provides infix operator o i |> abs |> Real.fromInt |> Math.sqrt fun sqrt_of_abs i = Math.sqrt(Real.fromInt(abs i)) fun sqrt_of_abs i = (Math.sqrt o Real.fromInt o abs) i val sqrt_of_abs = Math.sqrt o Real.fromInt o abs (F#, Microsoft's ML flavor, defines this by default) Right to left. Currying and Partial Application 3 Currying and Partial Application 4 Currying Example • Every ML function takes exactly one argument val sorted3 = fn x => fn y => fn z => z >= y andalso y >= x • Previously encoded n arguments via one n-tuple val t1 = ((sorted3 7) 9) 11 • Another way: 1. Calling (sorted3 7) returns closure #1 with: Take one argument and return a function that Code fn y => fn z => z >= y andalso y >= x takes another argument and… Environment: x ↦ 7 – Called “currying” after logician Haskell Curry 2. Calling closure #1 on 9 returns closure #2 with: Code fn z => z >= y andalso y >= x Environment: y ↦ 9, x ↦ 7 3.
    [Show full text]
  • CSE 341 : Programming Languages
    CSE 341 : Programming Languages Lecture 10 Closure Idioms Zach Tatlock Spring 2014 More idioms • We know the rule for lexical scope and function closures – Now what is it good for A partial but wide-ranging list: • Pass functions with private data to iterators: Done • Combine functions (e.g., composition) • Currying (multi-arg functions and partial application) • Callbacks (e.g., in reactive programming) • Implementing an ADT with a record of functions (optional) 2 Combine functions Canonical example is function composition: fun compose (f,g) = fn x => f (g x) • Creates a closure that “remembers” what f and g are bound to • Type ('b -> 'c) * ('a -> 'b) -> ('a -> 'c) but the REPL prints something equivalent • ML standard library provides this as infix operator o • Example (third version best): fun sqrt_of_abs i = Math.sqrt(Real.fromInt(abs i)) fun sqrt_of_abs i = (Math.sqrt o Real.fromInt o abs) i val sqrt_of_abs = Math.sqrt o Real.fromInt o abs 3 Left-to-right or right-to-left val sqrt_of_abs = Math.sqrt o Real.fromInt o abs As in math, function composition is “right to left” – “take absolute value, convert to real, and take square root” – “square root of the conversion to real of absolute value” “Pipelines” of functions are common in functional programming and many programmers prefer left-to-right – Can define our own infix operator – This one is very popular (and predefined) in F# infix |> fun x |> f = f x fun sqrt_of_abs i = i |> abs |> Real.fromInt |> Math.sqrt 4 Another example • “Backup function” fun backup1 (f,g) = fn x => case
    [Show full text]
  • Functional Programming at Work in Object-Oriented Programming
    Functional Programming at Work in Object-Oriented Programming Narbel version 2010 Narbel Functional Programming at Work in Object-Oriented Programming 1 A Claim about Programming Styles Claim: Adding functional programming capabilities to an object-oriented language leads to benefits in object-oriented programming design. Narbel Functional Programming at Work in Object-Oriented Programming 2 Existing Languages with a FP-OOP Mix Some old and less old languages with FP+OOP: For instance, Smalltalk, Common Lisp (CLOS). More recently, Python or Ruby. Notations: FP, Functional programming; OOP, Object-oriented programming, Narbel Functional Programming at Work in Object-Oriented Programming 3 FP techniques emulated in OOP Practices in OOP languages include emulations of FP techniques: C++ programmers: function pointers and overloadings of the () operator, i.e. “object-functions” or functors. Java programmers: anonymous classes and introspection/reflexion. Narbel Functional Programming at Work in Object-Oriented Programming 4 Existence of FP-OOP Comparison Points The idea of using FP to enrich OOP is old, see e.g. the discussions about the problem of the user-defined datatype extension: User-defined types and procedural data structures as complementary approaches to data abstraction. Reynolds. 1975. The Expression Problem. Wadler. 1998. Narbel Functional Programming at Work in Object-Oriented Programming 5 A Trend: FP Extensions for OO Languages A recent trend: to propose and include typed FP extensions in mainstream static OO languages. Extensions for C++ (see e.g. Laufer, Striegnitz, McNamara, Smaragdakis), and work in progress in the C++ standard committees. Java 7 expected to include FP constructs. C# offers FP constructs (even more in its 3.0 version).
    [Show full text]
  • Exploring Languages with Interpreters and Functional Programming Chapter 16
    Exploring Languages with Interpreters and Functional Programming Chapter 16 H. Conrad Cunningham 15 October 2018 Contents 16 Haskell Function Concepts 2 16.1 Chapter Introduction . .2 16.2 Strictness . .2 16.3 Currying and Partial Application . .3 16.4 Operator Sections . .4 16.5 Combinators . .5 16.6 Functional Composition . .7 16.7 Function Pipelines . .7 16.8 Lambda Expressions . .9 16.9 Application Operator $ ....................... 10 16.10Eager Evaluation Using seq and $! ................. 11 16.11What Next? . 12 16.12Exercises . 13 16.13Acknowledgements . 13 16.14References . 14 16.15Terms and Concepts . 14 Copyright (C) 2016, 2017, 2018, H. Conrad Cunningham Professor of Computer and Information Science University of Mississippi 211 Weir Hall P.O. Box 1848 University, MS 38677 (662) 915-5358 Browser Advisory: The HTML version of this textbook requires a browser that supports the display of MathML. A good choice as of October 2018 is a recent version of Firefox from Mozilla. 1 16 Haskell Function Concepts 16.1 Chapter Introduction The previous chapter introduced the concepts of first-class and higher-order functions and generalized common computational patterns to construct a library of useful higher-order functions to process lists. This chapter continues to examine those concepts and their implications for Haskell programming. It explores strictness, currying, partial application, com- binators, operator sections, functional composition, inline function definitions, evaluation strategies, and related methods. The Haskell module for this chapter is in FunctionConcepts.hs. 16.2 Strictness In the discussion of the fold functions, the previous chapter introduced the concept of strictness. In this section, we explore that in more depth.
    [Show full text]